1 citations · 2 across the 8 of their papers we have counts for
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Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling
Di Wu, Shicai Fan, Xue Zhou +4
Reconstruction-based methods have been commonly used for unsupervised anomaly detection, in which a normal image is reconstructed and compared with the given test image to detect a…
Variational Probabilistic Fusion Network for RGB-T Semantic Segmentation
Baihong Lin, Zengrong Lin, Yulan Guo +3
RGB-T semantic segmentation has been widely adopted to handle hard scenes with poor lighting conditions by fusing different modality features of RGB and thermal images. Existing me…
Cluster-aware Contrastive Learning for Unsupervised Out-of-distribution Detection
Menglong Chen, Xingtai Gui, Shicai Fan
Unsupervised out-of-distribution (OOD) Detection aims to separate the samples falling outside the distribution of training data without label information. Among numerous branches,…
Constrained Adaptive Projection with Pretrained Features for Anomaly Detection
Xingtai Gui, Di Wu, Yang Chang +1
Anomaly detection aims to separate anomalies from normal samples, and the pretrained network is promising for anomaly detection. However, adapting the pretrained features would be…